Biostatistics Modeling and Public Health Applications
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This book provides an overview and compilation of contemporary topics and innovative approaches in biostatistical modeling through their applications to evidence-based public health research and decision-making. This book covers topics in 3 parts as: 1) Biostatistical Modeling, 2) Imaging Data Analysis, and 3) Public Health Applications.
Topics should appeal to both expert statisticians, as well as health researchers interested in biostatistical methodological applications in evidence-based health research. The book is a resourceful manual and can be used as an authoritative reference. The…mehr

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Produktbeschreibung
This book provides an overview and compilation of contemporary topics and innovative approaches in biostatistical modeling through their applications to evidence-based public health research and decision-making. This book covers topics in 3 parts as: 1) Biostatistical Modeling, 2) Imaging Data Analysis, and 3) Public Health Applications.

Topics should appeal to both expert statisticians, as well as health researchers interested in biostatistical methodological applications in evidence-based health research. The book is a resourceful manual and can be used as an authoritative reference. The features covered in this book will appeal to researchers where public health research is being rigorously conducted.
Autorenporträt
Ding-Geng Chen is a fellow of the American Statistical Association and is currently the executive director and professor in biostatistics at the College of Health Solutions, Arizona State University. He is also an extraordinary professor and the SARChI research chair in biostatistics at the University of Pretoria, an honorary professor at the University of KwaZulu-Natal, South Africa. He is a senior biostatistics consultant for biopharmaceuticals and government agencies with extensive expertise in biostatistics, clinical trials, and public health statistics and data sciences. Dr. Chen has more than 200 referred professional publications, co-authored/co-edited 40 books on clinical trial methodology, meta-analysis, data science, causal inference, and public health research. DCarlos A. Coelho is a Full Professor of Statistics at the Mathematics Department of NOVA School of Science and Technology of NOVA University of Lisbon. He holds a Ph.D. in Biostatistics by The University of Michigan, Ann Arbor, MI, U.S.A., where he was a Fulbrighter. His main area of research is Multivariate Analysis, namely the development of likelihood ratio tests for elaborate covariance structures and for MANOVA models, also with elaborate covariance structures, together with the study of the exact distribution and the development of near-exact distributions for the associated test statistics. Related with this area, other areas of interest are Mathematical Statistics and Distribution Theory, as well as Estimation, Univariate and Multivariate Linear, Generalized Linear and Mixed Models. More recently, he tests for high-dimensionality and the application of Multivariate Analysis techniques to Statistical Disclosure Control problems. Carlos A. Coelho currently serves in the Editorial Boards of the Journal of Statistical Theory and Practice and the American Journal of Mathematical and Management Sciences. He is also Associate Editor of the Springer Book series "Emerging Topics in Statistics and Biostatistics" and a member of the International Council of the "Business World" Library of the Tsenov Academy of Economics (Svishtov, Bulgaria). Currently, Carlos A. Coelho also serves as President of Fulbrighters Portugal, the Portuguese Fulbright Alumni Association.